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Variational Inference

1946 directly classified papers

Papers per year

Papers

Improving Unsupervised Hierarchical Representation with Reinforcement Learning CVPR 2024
The Star Geometry of Critic-Based Regularizer Learning NIPS 2024
VSGT: Variational Spatial and Gaussian Temporal Graph Models for EEG-based Emotion Recognition IJCAI 2024
DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation NIPS 2024
DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions EMNLP 2024
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NIPS 2024
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling NIPS 2024
Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoders EACL 2024
HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NIPS 2024
Frogs into princes: A generative model to understand the success of product descriptions COLING 2024
VAE-based Phoneme Alignment Using Gradient Annealing and SSL Acoustic Features INTERSPEECH 2024
On Divergence Measures for Training GFlowNets NIPS 2024
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation AISTATS 2024
Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach AISTATS 2024
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform NIPS 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024
Towards Practical Non-Adversarial Distribution Matching AISTATS 2024
Variational Distillation of Diffusion Policies into Mixture of Experts NIPS 2024
Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024
Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds AISTATS 2024
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection NIPS 2024
Identifiable Feature Learning for Spatial Data with Nonlinear ICA AISTATS 2024
Variational Resampling AISTATS 2024
Generative Calibration of Inaccurate Annotation for Label Distribution Learning AAAI 2024
Diffusion Priors for Variational Likelihood Estimation and Image Denoising NIPS 2024